There is increasing evidence that the gut microbiota plays a major role in host health and disease. In this study, we examined whether perturbation of the maternal gut microbiota during pregnancy, induced by administration of non-absorbable antibiotics to pregnant dams, influences the behavior of offspring. Terminal restriction fragment length polymorphism analyses of fecal bacterial composition showed that the relative abundance of the bacterial order Lactobacillales was lower in offspring born from antibiotic-treated dams (20.7±3.4%) than in control offspring (42.1±6.2%) at P24, while the relative abundance of the bacterial family Clostridium subcluster XIVa was higher in offspring born from antibiotic-treated dams (34.2±5.0%) than in control offspring (16.4±3.3%). Offspring born from antibiotic-treated dams exhibited low locomotor activity in both familiar and novel environments, and preferred to explore in the peripheral area of an unfamiliar field at postnatal week 4. At postnatal weeks 7–8, no difference was observed in the level of locomotor activity between control offspring and offspring from antibiotic-treated dams, while the tendency for the offspring from antibiotic-treated dams to be less engaged in exploring the inside area was still observed. The behavioral phenotypes of the offspring from antibiotic-treated dams at postnatal week 4 could be rescued to a considerable extent through fostering of these offspring by normal dams from postnatal day 1. Although the detailed underlying mechanisms are not fully elucidated, the present results suggest that administration of non-absorbable antibiotics to pregnant dams to perturb the maternal gut microbiota during pregnancy leads to alterations in the behavior of their offspring.
In Hokkaido we have often experienced hazardous accidents, such as tower collapses and conductor breakage, caused by wet-snow accretion on transmission lines, and over many years have developed countermeasures for wet-snow accretion. Recently we have been developing a system to forecast areas where snow accretion may occur. We used the southern part of Hokkaido, divided into 5 km × 5 km meshes, as a forecast area; our predictions were hourly, 3–24 hours in advance. A method of predicting meteorological data which forms an important part of the system predicts three elements which influence wet-snow accretion: air temperature, precipitation, and wind direction and speed. We used an interpolation for predicting temperature and precipitation and a one-level, mesoscale model for diagnosing surface winds for wind direction and speed. By applying the method to many examples of wet-snow accretion, we checked the prediction of weather elements.
ABSTRACT. In Hokkaido we have often experienced hazardous accidents, such as tower collapses and conductor breakage, caused by wet-snow accretion on transmission lines, and over many years have developed countermeasures for wetsnow accretion. Recently we have been developing a system to forecast areas where snow accretion may occur. We used the southern part of Hokkaido, divided into 5 km X 5 km meshes, as a forecast area; our predictions were hourly, 3-24 hours in advance. A method of predicting meteorological data which forms an important part of the system predicts three elements which influence wet-snow accretion: air temperature, precipitation, and wind direction and speed. We used an interpolation for predicting temperature and precipitation and a one-level, mesoscale model for diagnosing surface winds for wind direction and speed. By applying the method to many examples of wet-snow accretion, we checked the prediction of weather elements.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.